Hyperspectral imaging (HSI) have become paramount in biomedical science. The power of the combination between traditional imaging and spectroscopy opens the possibility to address information inaccessible before. For bioimaging analysis of these data, the Phasor Plots are tools that help the field because of their straightforward approach. Thus it is becoming a key player in democratizing access to HSI, and improve open source software for bioimaging communities.
hsipy is a module for HSI data analysis using the phasor approach. The phasor approach was developed as model free method and relies on the Fourier Transform properties.
Considering an hyperspectral image stack, the fluorescence spectra at each pixel can be transformed in phasor coordinates (G (λ)) and (S (λ)) as described in the following equations. I(λ) represent the intensity at every wavelength (channel), n is the number of the harmonic and λ i the initial wavelength. The, x and y coordinates are plotted in the spectral phasor plot.
The angular position in the spectral phasor plot relates to the center of mass of the emission spectrum and the modulus depends on the spectrum’s full width at the half maximum (FWHM). For instance, if the spectrum is broad its location should be close to the center. Otherwise, if there is a red shift in the spectrum, its location will move counterclockwise toward increasing angle from position (1, 0). Spectral phasors have the same vector properties as lifetime phasors. A detailed description of the spectral phasor plot properties can be found in Malacrida et al. 1.
pip install hsipy
conda install hsipyThis funtion uses matplotlib for representation. It allows user to plot the dc image and its corresponding histogram. In the histogram window the user is expected to pick an intensity value which will threshold the phasor plot later. Next it shows the phasor plot, where you can pick the circle componentes, and will create and display the pseudocolor image and the respectives spectrums to each circle.
It allows to plot the dc image and the histogram where you can pick the cut off intensity to threshold the phasor and later its displays the pseudoclor image created with a Hue Saturation Value color scale related to the phase and modulation.
Contributions are always very well welcome. This project is a fist version of PhasorPy Library which intends to create an open-source and collaborative community between spectroscopy and fluorescence microscopy users with the same functionalities as SimFCS but accessible and self-sustainable in the long term as other Python libraries and communities.
[1] Malacrida, L., Gratton, E. & Jameson, D. M. Model-free methods to study membrane environmental probes: A comparison of the spectral phasor and generalized polarization approaches. Methods Appl. Fluoresc. 3, 047001 (2015).